Machine learning is a type of artificial intelligence in which a computer is configured to learn without necessarily being explicitly programmed. For example, a computer may be configured to search through data and look for patterns, and then automatically adjust the actions of the computer program based on the patterns found.
In some applications, machine learning may be used to make a prediction. This may be done by first training the computer using past data for which the outcome is known, which is called supervised learning. The computer may extract rules or relationships during the training period. Then, when new inputs arrive, the computer uses the extracted rules or relationships to make a prediction.
As an example, machine learning may be used to predict whether rain will occur on a given day. First, in the training phase, the computer may be provided with several data inputs. Each data input corresponds to a respective day in the past and indicates the average temperature for that day, the humidity at 8 AM of that day, the day of the year, and whether or not it actually rained that day. The machine learning method then looks for patterns in the input data and extracts rules or relationships between particular input data parameters, such as what the temperature was and what day of the year it was, and the result: rain or no rain. Once the training is completed, when a new set of input data is sent to the computer for a particular day, then the computer will return a prediction of whether rain will occur that day.